We use feedback wavefront shaping technology to realize the multi-point uniform light focusing in three-dimensional(3D) space through scattering media only by loading the optimal mask once.General 3D spatial focusing ...We use feedback wavefront shaping technology to realize the multi-point uniform light focusing in three-dimensional(3D) space through scattering media only by loading the optimal mask once.General 3D spatial focusing needs to load the optimal mask multiple times to realize the spatial movement of the focal point and the uniformity of multi-point focusing cannot be guaranteed.First,we investigate the effects of speckle axial correlation and different axial distances on 3D spatial multi-point uniform focusing and propose possible solutions.Then we use our developed non-dominated sorting genetic algorithm suitable for 3D spatial focusing(S-NSGA) to verify the experiment of multi-point focusing in 3D space.This research is expected to have potential applications in the fields of optical manipulation and optogenetics.展开更多
A 325 MHz aluminum prototype of a spatially periodic RF quadrupole focusing linac was developed at the Institute of Modern Physics,Chinese Academy of Sciences,as a promising candidate for the front end of a high-curre...A 325 MHz aluminum prototype of a spatially periodic RF quadrupole focusing linac was developed at the Institute of Modern Physics,Chinese Academy of Sciences,as a promising candidate for the front end of a high-current linac.It consists of an alternating series of crossbar H-type drift tubes and RF quadrupole sections.Owing to its special geometry,cavity fabrication is a major hurdle for its engineering development and application.In this paper,we report the detailed mechanical design of this structure and describe its fabrication process,including machining,assembly,and inspection.The field distribution was measured by the bead-pull technique.The results show that the field errors of both the accelerating and focusing fields are within an acceptable range.A tuning scheme for this new structure is proposed and verified.The cold test process and results are presented in detail.The development of this prototype provides valuable guidance for the application of the spatially periodic RF quadrupole structure.展开更多
The evolving field of Alzheimer’s disease(AD)diagnosis has greatly benefited from deep learning models for analyzing brain magnetic resonance(MR)images.This study introduces Dynamic GradNet,a novel deep learning mode...The evolving field of Alzheimer’s disease(AD)diagnosis has greatly benefited from deep learning models for analyzing brain magnetic resonance(MR)images.This study introduces Dynamic GradNet,a novel deep learning model designed to increase diagnostic accuracy and interpretability for multiclass AD classification.Initially,four state-of-the-art convolutional neural network(CNN)architectures,the self-regulated network(RegNet),residual network(ResNet),densely connected convolutional network(DenseNet),and efficient network(EfficientNet),were comprehensively compared via a unified preprocessing pipeline to ensure a fair evaluation.Among these models,EfficientNet consistently demonstrated superior performance in terms of accuracy,precision,recall,and F1 score.As a result,EfficientNetwas selected as the foundation for implementing Dynamic GradNet.Dynamic GradNet incorporates gradient weighted class activation mapping(GradCAM)into the training process,facilitating dynamic adjustments that focus on critical brain regions associated with early dementia detection.These adjustments are particularly effective in identifying subtle changes associated with very mild dementia,enabling early diagnosis and intervention.The model was evaluated with the OASIS dataset,which contains greater than 80,000 brain MR images categorized into four distinct stages of AD progression.The proposed model outperformed the baseline architectures,achieving remarkable generalizability across all stages.This findingwas especially evident in early-stage dementia detection,where Dynamic GradNet significantly reduced false positives and enhanced classification metrics.These findings highlight the potential of Dynamic GradNet as a robust and scalable approach for AD diagnosis,providing a promising alternative to traditional attention-based models.The model’s ability to dynamically adjust spatial focus offers a powerful tool in artificial intelligence(AI)assisted precisionmedicine,particularly in the early detection of neurodegenerative diseases.展开更多
Objective To investigate the spike activities of cerebellar cortical cells in a computational network model con- structed based on the anatomical structure of cerebellar cortex. Methods and Results The multicompartmen...Objective To investigate the spike activities of cerebellar cortical cells in a computational network model con- structed based on the anatomical structure of cerebellar cortex. Methods and Results The multicompartment model of neuron and NEURON software were used to study the external influences on cerebellar cortical cells. Various potential spike patterns in these cells were obtained. By analyzing the impacts of different incoming stimuli on the potential spike of Purkinje cell, temporal focusing caused by the granule cell-golgi cell feedback inhibitory loop to Purkinje cell and spa- tial focusing caused by the parallel fiber-basket/stellate cell local inhibitory loop to Purkinje cell were discussed. Finally, the motor learning process of rabbit eye blink conditioned reflex was demonstrated in this model. The simulation results showed that when the afferent from climbing fiber existed, rabbit adaptation to eye blinking gradually became stable under the Spike Timing-Dependent Plasticity （STDP） learning rule. Conclusion The constructed cerebellar cortex network is a reliable and feasible model. The model simulation results confirmed the output signal stability of cerebellar cortex after STDP learning and the network can execute the function of spatial and temporal focusing.展开更多
The generation of tunably focused light at remote locations is a critical photonic functionality for a wide range of applications.Here,we present a novel concept in the emerging field of Metafibers that achieves,for t...The generation of tunably focused light at remote locations is a critical photonic functionality for a wide range of applications.Here,we present a novel concept in the emerging field of Metafibers that achieves,for the first time,fast,alignment-free,fiber-integrated spatial focus control in a monolithic arrangement.This is enabled by 3D nanoprinted intensity-sensitive phase-only on-fiber holograms,which establish a direct correlation between the intensity distribution in the hologram plane and the focus position.Precise adjustment to the relative power between the modes of a dual-core fiber generates a power-controlled interference pattern within the hologram,enabling controlled and dynamic focus shifts.This study addresses all relevant aspects,including computational optimization,advanced 3D nanoprinting,and tailored fiber fabrication.Experimental results supported by simulations validate the feasibility and efficiency of this monolithic Metafiber platform,which enables fast focus modulation and has transformative potential in optical manipulation,high-speed laser micromachining,telecommunications,and minimally invasive surgery.展开更多
This paper reviewed the developments of the last ten years in the field of international high-resolution earth observation, and introduced the developmental status and plans for China's high-resolution earth obser...This paper reviewed the developments of the last ten years in the field of international high-resolution earth observation, and introduced the developmental status and plans for China's high-resolution earth observation program. In addition, this paper expounded the transformation mechanism and procedure from earth observation data to geospatial information and geographical knowledge, and examined the key scientific and technological issues, including earth observation networks, high-precision image positioning, image understanding, automatic spatial information extraction, and focus services. These analyses provide a new impetus for pushing the application of China's high-resolution earth observation system from a "quantity" to "quality" change, from China to the world, from providing products to providing online service.展开更多
基金Project supported by the Natural Science Foundation of Beijing Municipality,China(Grant No.7182091)。
文摘We use feedback wavefront shaping technology to realize the multi-point uniform light focusing in three-dimensional(3D) space through scattering media only by loading the optimal mask once.General 3D spatial focusing needs to load the optimal mask multiple times to realize the spatial movement of the focal point and the uniformity of multi-point focusing cannot be guaranteed.First,we investigate the effects of speckle axial correlation and different axial distances on 3D spatial multi-point uniform focusing and propose possible solutions.Then we use our developed non-dominated sorting genetic algorithm suitable for 3D spatial focusing(S-NSGA) to verify the experiment of multi-point focusing in 3D space.This research is expected to have potential applications in the fields of optical manipulation and optogenetics.
基金This work was supported by the NSAF Joint Foundation of China(No.U1730122)。
文摘A 325 MHz aluminum prototype of a spatially periodic RF quadrupole focusing linac was developed at the Institute of Modern Physics,Chinese Academy of Sciences,as a promising candidate for the front end of a high-current linac.It consists of an alternating series of crossbar H-type drift tubes and RF quadrupole sections.Owing to its special geometry,cavity fabrication is a major hurdle for its engineering development and application.In this paper,we report the detailed mechanical design of this structure and describe its fabrication process,including machining,assembly,and inspection.The field distribution was measured by the bead-pull technique.The results show that the field errors of both the accelerating and focusing fields are within an acceptable range.A tuning scheme for this new structure is proposed and verified.The cold test process and results are presented in detail.The development of this prototype provides valuable guidance for the application of the spatially periodic RF quadrupole structure.
基金funded by Taif University,Saudi ArabiaThe author would like to acknowledge Deanship of Graduate Studies and Scientific Research,Taif University for funding this work.
文摘The evolving field of Alzheimer’s disease(AD)diagnosis has greatly benefited from deep learning models for analyzing brain magnetic resonance(MR)images.This study introduces Dynamic GradNet,a novel deep learning model designed to increase diagnostic accuracy and interpretability for multiclass AD classification.Initially,four state-of-the-art convolutional neural network(CNN)architectures,the self-regulated network(RegNet),residual network(ResNet),densely connected convolutional network(DenseNet),and efficient network(EfficientNet),were comprehensively compared via a unified preprocessing pipeline to ensure a fair evaluation.Among these models,EfficientNet consistently demonstrated superior performance in terms of accuracy,precision,recall,and F1 score.As a result,EfficientNetwas selected as the foundation for implementing Dynamic GradNet.Dynamic GradNet incorporates gradient weighted class activation mapping(GradCAM)into the training process,facilitating dynamic adjustments that focus on critical brain regions associated with early dementia detection.These adjustments are particularly effective in identifying subtle changes associated with very mild dementia,enabling early diagnosis and intervention.The model was evaluated with the OASIS dataset,which contains greater than 80,000 brain MR images categorized into four distinct stages of AD progression.The proposed model outperformed the baseline architectures,achieving remarkable generalizability across all stages.This findingwas especially evident in early-stage dementia detection,where Dynamic GradNet significantly reduced false positives and enhanced classification metrics.These findings highlight the potential of Dynamic GradNet as a robust and scalable approach for AD diagnosis,providing a promising alternative to traditional attention-based models.The model’s ability to dynamically adjust spatial focus offers a powerful tool in artificial intelligence(AI)assisted precisionmedicine,particularly in the early detection of neurodegenerative diseases.
基金supported by the grants from National Natural Science Foundation of China (No. 10872069)
文摘Objective To investigate the spike activities of cerebellar cortical cells in a computational network model con- structed based on the anatomical structure of cerebellar cortex. Methods and Results The multicompartment model of neuron and NEURON software were used to study the external influences on cerebellar cortical cells. Various potential spike patterns in these cells were obtained. By analyzing the impacts of different incoming stimuli on the potential spike of Purkinje cell, temporal focusing caused by the granule cell-golgi cell feedback inhibitory loop to Purkinje cell and spa- tial focusing caused by the parallel fiber-basket/stellate cell local inhibitory loop to Purkinje cell were discussed. Finally, the motor learning process of rabbit eye blink conditioned reflex was demonstrated in this model. The simulation results showed that when the afferent from climbing fiber existed, rabbit adaptation to eye blinking gradually became stable under the Spike Timing-Dependent Plasticity （STDP） learning rule. Conclusion The constructed cerebellar cortex network is a reliable and feasible model. The model simulation results confirmed the output signal stability of cerebellar cortex after STDP learning and the network can execute the function of spatial and temporal focusing.
基金German Research Foundation(DFG)via the grants SCHM2655/21-1,SCHM2655/23-1,QI 140/2-1。
文摘The generation of tunably focused light at remote locations is a critical photonic functionality for a wide range of applications.Here,we present a novel concept in the emerging field of Metafibers that achieves,for the first time,fast,alignment-free,fiber-integrated spatial focus control in a monolithic arrangement.This is enabled by 3D nanoprinted intensity-sensitive phase-only on-fiber holograms,which establish a direct correlation between the intensity distribution in the hologram plane and the focus position.Precise adjustment to the relative power between the modes of a dual-core fiber generates a power-controlled interference pattern within the hologram,enabling controlled and dynamic focus shifts.This study addresses all relevant aspects,including computational optimization,advanced 3D nanoprinting,and tailored fiber fabrication.Experimental results supported by simulations validate the feasibility and efficiency of this monolithic Metafiber platform,which enables fast focus modulation and has transformative potential in optical manipulation,high-speed laser micromachining,telecommunications,and minimally invasive surgery.
基金supported by National Basic Research Program of China(Grant No. 2012CB719906)
文摘This paper reviewed the developments of the last ten years in the field of international high-resolution earth observation, and introduced the developmental status and plans for China's high-resolution earth observation program. In addition, this paper expounded the transformation mechanism and procedure from earth observation data to geospatial information and geographical knowledge, and examined the key scientific and technological issues, including earth observation networks, high-precision image positioning, image understanding, automatic spatial information extraction, and focus services. These analyses provide a new impetus for pushing the application of China's high-resolution earth observation system from a "quantity" to "quality" change, from China to the world, from providing products to providing online service.
